Providing mediated social interactions

ABSTRACT

Systems and methods of providing mediated social interactions are provided. For instance, a user input from a first user indicative of a request to facilitate a provision of emotive contextual signals to a second user can be received. One or more emotive contextual signals to be provided to the second user can be determined based at least in part on the user input. The one or more emotive contextual signals can include one or more haptic feedback signals intended to facilitate a mediated social interaction associated with the second user.

PRIORITY CLAIM

The present application is based upon and claims the right of priorityunder 35 U.S.C. § 371 to International Application No.PCT/US2017/062665, filed on Nov. 21, 2017, which claims the benefit ofU.S. Provisional Application Ser. No. 62/425,737 filed Nov. 23, 2016.Applicant claims priority to and the benefit of each of suchapplications and incorporate all such applications herein by referencein its entirety.

FIELD

The present disclosure relates generally to providing mediated socialinteractions by one or more computing devices.

BACKGROUND

Humans use their sense of touch to interact with their environments.Such sense of touch can provide useful information regarding spatialaspects of the environment. For instance, the sense of touch can provideinformation relating to the position and movement of a person's body inspace. As another example, the sense of touch can provide informationrelating to the size, weight, shape, texture, etc. of external object.The sense of touch is particularly useful in social interactions.Contact with another human can evoke strong positive and negativeemotional experiences. Human touch can facilitate personal and intimateinterpersonal interaction, and can evoke a sense of proximity andconnectedness between humans.

Human touch can be simulated using mediated social interactiontechniques, wherein various forms of human contact are simulated, forinstance, via human-computer interaction systems, teleoperation systems,sensory substitution systems, and other suitable systems. Such systemscan allow users to viscerally experience such simulated human contactthrough the application of various signals to the users. In this manner,mediated social interaction systems can evoke various emotional orbiometric responses associated with human contact in the users.

SUMMARY

Aspects and advantages of embodiments of the present disclosure will beset forth in part in the following description, or may be learned fromthe description, or may be learned through practice of the embodiments.

One example aspect of the present disclosure is directed to acomputer-implemented method of providing emotive contextual signals to auser. The method includes receiving, by a first computing device, a userinput from a first user indicative of a request to facilitate aprovision of emotive contextual signals to a second user. The methodfurther includes determining, by a second computing device, one or moreemotive contextual signals to be provided to the second user based atleast in part on the user input, the one or more first emotivecontextual signals comprising one or more first haptic feedback signals.The first haptic feedback signals may, for example, facilitate or beintended to facilitate a mediated social interaction associated with thesecond user.

Other example aspects of the present disclosure are directed to systems,apparatus, tangible, non-transitory computer-readable media, userinterfaces, memory devices, and electronic devices for providing emotivecontextual signals.

These and other features, aspects and advantages of various embodimentswill become better understood with reference to the followingdescription and appended claims. The accompanying drawings, which areincorporated in and constitute a part of this specification, illustrateembodiments of the present disclosure and, together with thedescription, serve to explain the related principles.

BRIEF DESCRIPTION OF THE DRAWINGS

Detailed discussion of embodiments directed to one of ordinary skill inthe art are set forth in the specification, which makes reference to theappended figures, in which:

FIG. 1 depicts an example system for providing emotive contextualsignals according to example embodiments of the present disclosure;

FIG. 2 depicts an example system for providing emotive contextualsignals according to example embodiments of the present disclosure;

FIG. 3 depicts an example method of providing emotive contextual signalsaccording to example embodiments of the present disclosure;

FIG. 4 depicts an example method of determining emotive contextualsignals according to example embodiments of the present disclosure; and

FIG. 5 depicts an example system according to example embodiments of thepresent disclosure.

DETAILED DESCRIPTION

Reference now will be made in detail to embodiments, one or moreexamples of which are illustrated in the drawings. Each example isprovided by way of explanation of the embodiments, not limitation of thepresent disclosure. In fact, it will be apparent to those skilled in theart that various modifications and variations can be made to theembodiments without departing from the scope or spirit of the presentdisclosure. For instance, features illustrated or described as part ofone embodiment can be used with another embodiment to yield a stillfurther embodiment. Thus, it is intended that aspects of the presentdisclosure cover such modifications and variations.

Example aspects of the present disclosure are directed to providingemotive contextual signals to a user. For instance, a first user caninteract with a first interactive device to facilitate a provision of amediated social interaction with a second user of a second interactivedevice. For instance, the mediated social interaction can be a mediatedphysical interaction. Such mediated interaction can be intended tosimulate a physical action performed with respect to the second userand/or to evoke a desired emotional response by the second user. Thefirst user can perform an input gesture or other physical interactionwith respect to the first interactive device. One or more emotivecontextual signals can be determined based at least in part on theinteraction with the first interactive device by the first user. The oneor more emotive contextual signals can be, for instance, haptic feedbacksignals that, when provided to the second user, are intended to simulatean action performed with respect to the second user and/or to evoke anemotional response by the second user. In this manner, the one or moreemotive contextual signals can be provided to the second user by thesecond interactive device with the object of simulating the desiredaction and/or evoking the desired emotional response associated with theinteraction by the first user with the first interactive device.

As used herein, the term “input gesture” can refer to any suitableinteraction between a user and an associated interactive device thatfacilitates a provision of emotive contextual signals to a differentuser of an interactive device. For instance, the input gesture can be aparticular movement pattern of a hand or other input object associatedwith the user performed proximate the first interactive device (e.g.motion gesture), an actuation of the first interactive device by theuser (e.g. actuation of an input device associated with the interactivedevice), a particular movement or movement pattern of the firstinteractive device by the user (e.g. moving the interactive device in aparticular manner), a touch gesture performed on a surface of the firstinteractive device, an application of pressure to one or more areas ofthe interactive device, and/or other suitable interaction. In someimplementations, the input gesture performed by the first user can beassociated with a particular emotional response that the first userdesires to evoke in the second user. In some implementations, the inputgesture can be associated with a particular simulated action or behaviorthat the first user desires to be performed on the second user.

The first and second interactive devices can be any suitable computingdevice capable of detecting an input gesture and/or providing emotivecontextual signals to a user in accordance with example embodiments ofthe present disclosure. For instance, the interactive devices can eachbe a general purpose computer, special purpose computer, laptop,desktop, mobile device, navigation system, smartphone, tablet, wearablecomputing device (e.g. smart garment in accordance with example aspectsof the present disclosure, fitness band, smart watch, etc.), a displaywith one or more processors, or other suitable computing device. In thisregard, the first and second interactive devices can include one or moregesture detection sensors. The one or more gesture detection sensors canbe configured to detect a suitable input gesture performed by a userwith respect to the interactive device. For instance, the one or moregesture detection sensors can include pressure sensors, accelerometers,gyroscopes, magnetometers, inertial measurement units, radar devices,imaging devices, and/or other suitable gesture detection sensors. Thefirst and second interactive devices can further include one or morehaptic feedback devices configured to provide emotive contextual signalsto a user of the interactive devices. For instance, the one or morehaptic feedback devices can include one or more actuators (e.g.vibrotactile actuators, electrotactile actuators, piezoelectricactuators, electromechanical actuators, linear actuators, linearresonant actuators, etc.), motors (e.g. eccentric rotating mass motor,etc.), transducers (e.g. vibrotactile transducers), and/or othersuitable haptic feedback device. In this manner, the haptic feedbackdevices can be configured to provide physical stimuli to the user.

In some implementations, an interactive device in accordance withexample aspects of the present disclosure can be implemented within, orotherwise associated with a smart garment that is configured to be wornby the user. For instance, the smart garment can be constructed with aplurality of electrically conductive yarns, as described in greaterdetail below. Such electrically conductive yarns can be electricallycoupled to one or more suitable computing devices and can form one ormore circuits configured to implement example aspects of the presentdisclosure.

According to example aspects of the present disclosure, a user of afirst interactive device can interact with the first interactive deviceby performing an input gesture with respect to the first interactivedevice. A detection of the performance of the input gesture canfacilitate a provision of one or more emotive contextual signals to auser of a second interactive device by the second interactive device.The input gesture can be mapped to a particular emotional response orsimulated behavior. The simulated action and/or emotional response canbe associated with a mediated social touch performed on the second userby the second interactive device. For instance, a first input gesturecan be mapped to an evocation of a soothing feeling, and a secondinteraction can be mapped to an action that simulates a particular typeof touch, such as holding hands. In some implementations, the inputgesture mapping can be defined by a predefined gesture mapping schemethat respectively maps a plurality of input gestures to a plurality ofemotional responses and/or simulated actions.

In this manner, in response to a detection of a performance of an inputgesture by the first user, one or more emotive contextual signals can bedetermined based on the performed input gesture. For instance, theemotive contextual signals can be determined such that, when provided tothe second user, the second user experiences the desired mediatedinteraction associated with the detected input gesture. For instance,such emotive contextual signals can be haptic feedback signals appliedto the second user by the second interactive device. Such hapticfeedback signals can be associated with various suitable physicalstimuli, such as applied pressure, vibration, temperature, etc. In someimplementations, the haptic feedback signals can be an application of anelectrical current to the skin of the second user. As indicated, theemotive contextual signals can be determined based at least in part onthe mediated social interaction associated with the detected inputgesture. In this manner, the emotive contextual signals can be appliedto the user to evoke the intended emotional response and/or to simulatethe intended action with respect to the second user.

In some implementations, a mediated social interaction can be explicitlymapped to one or more particular emotive contextual signals, such that aparticular input gesture facilitates a provision of such particularemotive contextual signals. In this manner, a detection of an inputgesture performed by a first user can facilitate a provision of one ormore specific emotive contextual signals to a second user. In someimplementations, the emotive contextual signals can be determined basedat least in part on one or more characteristics of the second user. Forinstance, one or more biometric signals associated with the second usercan be monitored. The emotive contextual signals can be determined basedat least in part on the biometric signals. For instance, the biometricsignals can include one or more of a heart rate of the second user, atemperature of the second user, a skin conductance of the second user,and/or other suitable biometric signal. In this manner, the emotivecontextual signals can be personalized for the second user based atleast in part on the biometric characteristics of the second user.

In some implementations, the emotive contextual signals provided to thesecond user can be adjusted based at least in part on the biometricsignals of the second user. For instance, the biometric signals can bemonitored in response to a provision of the emotive contextual signalsto determine if the provision of the emotive contextual signals ishaving the desired effect on the second user. For instance, themonitored biometric signals can be compared to target biometric signalsassociated with the simulated action and/or the emotional responseassociated with the emotive contextual signals. As another example abiometric response (e.g. a change in biometric signals in response to areception of the emotive contextual signals) can be compared to a targetbiometric response associated with the simulated action and/or theemotional response associated with the emotive contextual signals. Inthis manner, if the user reacts to the emotive contextual signals in amanner inconsistent with the aim of the emotive contextual signals, theemotive contextual signals can be adjusted to facilitate the desiredresult.

In some implementations, the emotive contextual signals can bedetermined using one or more machine learning techniques. For instance,data associated with a response of a user to a reception of emotivecontextual signals can be used by a suitable machine learning model to“learn” personalized emotive contextual signals that evoke the desiredresponse in the user. Any suitable machine learning model can be used,such as neural networks (e.g., deep neural networks) or othermulti-layer non-linear models. Neural networks can include recurrentneural networks (e.g., long short-term memory recurrent neuralnetworks), feed-forward neural networks, or other forms of neuralnetworks. For instance, the machine learning model can receive as inputthe target emotional response and/or simulated action, and the machinelearning model can provide as output the emotive contextual signals tobe provided to the user. The machine learning model can be trained usingsuitable training data to adjust the model based, for instance, on thebiometric characteristics of the second user. For instance, thebiometric signals and/or biometric response of the user subsequent to aprovision of the emotive contextual signals can be compared againsttarget biometric signals and/or biometric response associated with theemotive contextual signals. The machine learning model can be adjustedbased at least in part on the comparison. In this manner, the machinelearning techniques can be used to personalize the emotive contextualsignals towards the second user.

In this manner, the first and second interactive devices can be usedrespectively by the first and second users to facilitate a mediatedsocial interaction between the users. For instance, the first user andthe second user can each use their respective interactive devices tosend and receive emotive contextual signals to the other user. Suchmediated social interaction can allow the users to use their senses oftouch in the interaction via the interactive devices. Such mediatedinteractions can help to establish a sense of connectedness between theusers, and/or to provide various psychological benefits that accompanyphysical interactions (e.g. direct contact) between humans, such as asense of intimacy, recovery from stress, calming sensations, and/orother suitable emotional responses. In this manner, the provisions ofthe emotive contextual signals can simulate such physical interactions.

With reference now to the figures, example aspects of the presentdisclosure will be discussed in greater detail. For instance, FIG. 1depicts an example system (100) for providing emotive contextual signalsaccording to example embodiments of the present disclosure. System 100includes a first interactive device 102 and a second interactive device104. The first interactive device 102 includes an input gesture detector106 and a signal determiner 108. Similarly, the second interactivedevice includes an input gesture detector 110 and a signal determiner112. The first interactive device 102 can be associated with a firstuser and the second interactive device 104 can be associated with asecond user. The first and second users can respectively use the firstand second interactive devices 102 and 104 to facilitate mediated socialinteractions between the users. In this manner, the first user canperform an input gesture with respect to the first interactive device102. The input gesture detector can be configured to detect theperformance of the input gesture, for instance, using one or moredetection sensors 114. The input gesture can be any suitable inputgesture, such as a touch gesture performed on a surface of the firstinteractive device 102, an application of pressure to the firstinteractive device 102, a causation of movement of the first interactivedevice 102 in a predefined manner (e.g. shaking, rotating, etc. thefirst interactive device 102), a motion gesture performed proximate thefirst interactive device 102 (e.g. an in-air hand gesture, and/or anin-air gesture performed with an input object such as a stylus), or anyother suitable input gesture.

The detection sensor(s) 114 can be implemented within or otherwiseassociated with the first interactive device, and can include anysuitable sensors or other gesture detection devices configured to detecta performance of a suitable input gesture. For instance, the detectionsensor(s) can include one or more pressure sensors (e.g. capacitivepressure sensors, piezoresistive pressure sensors, electromagneticpressure sensors, optical pressure sensors, potentiometric pressuresensors, piezoelectric pressure sensors, etc.), position sensors (e.g.accelerometers, gyroscopes, inertial measurement units, etc.), imagingsensors (e.g. optical imaging sensors, radar imaging sensors, LIDARimaging sensors, etc.), and/or other suitable devices.

The input gesture can be associated with a mediated social interactionto be established between the first and the second user. Suchassociation can be defined by a predefined gesture mapping scheme thatrespectively corresponds a plurality of suitable input gestures to aplurality of suitable mediated social interactions. For instance, themediated social interaction can be a mediated physical interaction (e.g.a particular mediated social touch), such as a simulation of holdinghands, a simulation of a body hug, a simulation of any other suitableform of physical interaction between humans. In this manner, themediated social interaction can be associated with an application of anysuitable emotive contextual signals intended to simulate the particularmediated social touch on the first or second user. In someimplementations, rather than a particular form of touch, the mediatedsocial interaction can be an evocation of a particular emotionalresponse. In this manner, the mediated social interaction can beassociated with an application of any suitable emotive contextualsignals intended to evoke such particular emotional response in thefirst or second user.

In some implementations, data indicative of the detected input gesturecan be provided to the second interactive device 104. As will bedescribed in more detail with regard to FIG. 2, the communicationbetween the first interactive device 102 and the second interactivedevice 104 can be implemented by way of one or more networks and one ormore relaying devices. Upon receipt of the data indicative of thedetected input gesture, the second interactive device 104 can determineone or more emotive contextual signals to be provided to the second userbased at least in part on the detected input gesture. For instance, thesignal determiner 112 can access the predefined gesture mapping schemeto determine the mediated social interaction associated with the userinput. In this manner, the signal determiner 112 can determine themediated social interaction that the first user desires to establishbetween the first and second user.

Upon a determination of the mediated social interaction, the signaldeterminer 112 can determine one or more emotive contextual signals tobe provided to the second user. The one or more emotive contextualsignals can be any suitable signal that implements the specifiedmediated social interaction. For instance, the emotive contextualsignals can be haptic feedback signals that can be provided to the uservia one or more haptic feedback devices 122. For instance, the hapticfeedback devices 122 can include one or more actuators (e.g.vibrotactile actuators, electrotactile actuators, piezoelectricactuators, electromechanical actuators, linear actuators, linearresonant actuators, etc.), motors (e.g. eccentric rotating mass motor,etc.), transducers (e.g. vibrotactile transducers), and/or othersuitable haptic feedback device. In this regard, the haptic feedbacksignals can include vibration, pressure, temperature (e.g. heat orwarmth), electrical currents, forces, stress, strain, impacts, and/orother suitable forms of haptic feedback or physical stimulations. Moreparticularly, the emotive contextual signals can be haptic feedbacksignals having varying parameters (e.g. magnitudes, frequencies, etc.).For instance, an emotive contextual signal can be an application of aparticular amount of pressure, or a vibration having a particularfrequency and/or magnitude.

The emotive contextual signals can be determined based at least in parton the specified mediated social interaction. For instance, in someimplementations, the emotive contextual signals can be universal ordefault emotive contextual signals that correspond to specified mediatedsocial interaction. In this manner, each mediated social interactionspecified within the gesture mapping scheme can be further mapped to oneor more emotive contextual signals intended to simulate the mediatedsocial interaction. In some implementations, the emotive contextualsignals can be personalized for the second user. For instance, theemotive contextual signals intended to simulate the mediated socialinteraction can be determined based at least in part on one or morebiometric characteristics of the second user. In this manner, one ormore biometric monitors 122 can be configured to monitor one or morebiometric signals of the second user. The biometric monitor(s) can beany suitable devices configured to determine such biometric signals. Forinstance, the biometric monitor(s) 122 can be configured to monitor aheart rate of the second user, a temperature of the second user, a skinconductance of the second user, etc.

In this manner, the signal determiner 112 can determine the one or moreemotive contextual signals by taking into account the biometriccharacteristics of the second user. For instance, the biometriccharacteristics of the second user can be used to tailor the emotivecontextual signals to the user. In this manner, the emotive contextualsignals determined for a particular mediated social interaction for aparticular user can depend on the biometric characteristics of the user.In some implementations, the signal determiner 112 can determine the oneor more emotive contextual signals to evoke a particular biometricresponse in the user. For instance, the emotive contextual signals canbe determined such that an application of the emotive contextual signalsto the second user is intended to lower the second user's heart rate. Insome implementations, the personalized emotive contextual signals can bedetermined by adjusting the default or universal emotive contextualsignals associated with a particular mediated social interaction basedon the monitored biometric signals of the second user.

Upon a determination of the emotive contextual signals, the emotivecontextual signals can be provided to the second user via the hapticfeedback device(s) 122. As indicated, the emotive contextual signals canbe haptic feedback signals, such as vibration, pressure, temperature(e.g. heat or warmth), electrical currents, forces, stress, strain,impacts, and/or other suitable forms of haptic feedback or physicalstimulations. The haptic feedback devices may provide such signals tothe second user, for instance, while the second user is making contactwith the second interactive device 104.

Various users may react differently to a reception of various emotivecontextual signals. In this manner, in some implementations, thebiometric monitor(s) 124 can continue to monitor the biometric signalsof the second user during the application of the emotive contextualsignals and/or subsequent to the application of the emotive contextualsignals. In such implementations, the second interactive device 104 canuse such monitored signals to determine if the emotive contextualsignals are having the desired effect on the second user. For instance,the monitored biometric signals can be compared to target biometricsignals associated with the mediated social interaction to determine ifthe emotive contextual signals are having the desired effect. In someimplementations, the biometric reaction (e.g. change in heart rate, bodytemperature, etc.) of the user can be compared to a target biometricreaction or target emotional response. If the biometric reaction of theuser does not match the target biometric reaction, the emotivecontextual signals can be adjusted to attempt to evoke the targetbiometric reaction.

In some implementations, the biometric reactions of a user to aprovision of various emotive contextual signals can be tracked over timeto learn the preferences and characteristics of the user. For instance,example aspects of the present disclosure can include learning how suchuser reacts to various emotive contextual signals. The learned reactionscan be used to determine personalized emotive contextual signals to beprovided to the user to facilitate various mediated social interactions.For instance, the emotive contextual signals provided to the user tofacilitate various mediated social interactions can be adjusted overtime based on the reaction of the user to the provision of such emotivecontextual signals. The adjustments can be made to more accuratelyfacilitate the mediated social interactions between users. In someimplementations, such adjustments can be made using one or more machinelearning techniques. For instance, a machine learning model (e.g. neuralnetwork or other model) can be used to learn the user's preferences andto determine the personalized emotive contextual signals.

In this manner, the first interactive device 102 and the secondinteractive device 104 can be used by the first user and the second userto facilitate mediated social interactions between the first and secondusers. Although the above examples described the first user facilitatinga provision of emotive contextual signals to the second user, it will beappreciated that the second user may also use the second interactivedevice 104 to facilitate a provision of emotive contextual signals tothe first user. For instance, the second user may perform an inputgesture, and the input gesture detector 110 can detect such performanceof the input gesture using one or more detection sensors 120. Similar tothe detection sensor(s) 114, the detection sensor(s) 120 can include oneor more pressure sensors, position sensors, imaging sensors, etc. Thesignal determiner 108 of the first interactive device 102 can determineone or more emotive contextual signals based at least in part on theinput gesture detected by the input gesture detector 110. The emotivecontextual signals can be provided to the first user via one or morehaptic feedback devices 116. Similar to the haptic feedback device(s)122 of the second interactive device 104, the haptic feedback device(s)116 can include one or more actuators, motors, vibration engines,temperature applicators, etc. configured to apply haptic feedbacksignals to the first user. In some implementations, the emotivecontextual signals can be determined based at least in part on one ormore biometric characteristics of the first user monitored by one ormore biometric monitors 118.

The first interactive device 102 and the second interactive device 104can be any suitable computing devices capable of detecting an inputgesture and/or providing emotive contextual signals to a user inaccordance with example embodiments of the present disclosure. Forinstance, the interactive devices can each be a general purposecomputer, special purpose computer, laptop, desktop, mobile device,navigation system, smartphone, tablet, wearable computing device, adisplay with one or more processors, or other suitable computing device.More particularly, the interactive devices 102, 104 can be devicescapable of applying suitable emotive contextual signals to a user whilein physical contact with a user. The interactive devices can beconfigured such that a user can grip, hold, wear, press up against, etc.at least a portion of the interactive device to receive the emotivecontextual signals provided by the interactive device. In this manner,the form factor of the interactive device can be designed to facilitatesuch provision of emotive contextual signals.

In some implementations, the interactive device 102 and/or theinteractive device 104 can be smart garments constructed usingelectrically conductive yarns. Fabric structures, such as garments, madein accordance with the present disclosure are generally formed fromyarns that are woven or knitted together. In one embodiment, at leastcertain of the yarns are electrically conductive. The electricallyconductive yarns can be woven into the fabric structure in order to formvarious different electronic circuits. Various different types ofelectrical devices can be attached to the yarns and controlled by acontroller, such as a microprocessor. In one embodiment, the entirefabric structure can be made from electrically conductive yarns. In analternative embodiment, however, the fabric structure can be acombination of conductive yarns and non-conductive yarns. When combiningconductive yarns and non-conductive yarns, a fabric can be produced thathas the feel, drape characteristics, and other properties of typicalfabrics used to produce garments and the like. Thus, the electricallyconductive yarns can be incorporated into the fabric without undesirablyincreasing stiffness or imparting any other undesirable characteristicsinto the fabric.

In general, conductive yarns for use in fabrics of the presentdisclosure can be made from any suitable conductive material. Theconductive material, for instance, may comprise a metal, a metalliccompound, a conductive polymer, or mixtures thereof. The yarn cancomprise a monofilament yarn, a multifilament yarn, and possibly a spunyarn. In one embodiment, for instance, the conductive yarns comprisemonofilament yarns. The entire yarn can be made from a conductivematerial. Alternatively, the yarn may comprise a multicomponent yarncontaining a conductive component and a non-conductive component. Forinstance, in one embodiment, the multicomponent yarn may comprise abicomponent yarn in which the conductive component comprises the coresurrounded by a non-conductive sheath. Alternatively, the conductivecomponent may comprise the sheath while the non-conductive component maycomprise the core. In still another embodiment, the conductive componentand the non-conductive component can be in a side-by-side relationshipwithin the yarn.

In one embodiment, the conductive yarn comprises a core-sheath typeconductive fiber, such as a monofilament fiber containing a core madefrom a conductive polymer. For instance, the conductive polymer used tomake the core may comprise an acetylene conductive polymer, a pyrroleconductive polymer, a thiophene-based conductive polymer, a phenyleneconductive polymer, an aniline conductive polymer, or the like.

For example, the conductive portion of the fiber may comprise anacetylene-based, 5-membered heterocyclic system. Monomers that may beused to produce the conductive polymer include, for instance,3-methylpyrrole, 3-ethylpyrrole, 3-dodecylpyrrole 3-alkylpyrrole,3,4-dimethylpyrrole, 3-methyl-4-3,4-dialkylpyrrole, dodecylpyrrole,N-methylpyrrole, N-alkylpyrrole such as N-dodecylpyrrole,N-methyl-3-methylpyrrole, N-alkyl-3-alkylpyrrole such asN-ethyl-3-dodecylpyrrole, 3-carboxymethylpyrrole, and the like. In analternative embodiment, the conductive polymer may comprise athiophene-based polymer such as an isothianaphthene-based polymer. Otherexamples of thiophene-based conductive polymers includepoly-3,4-ethylene dioxythiophene. An example of a phenylene conductivepolymer is poly-p-phenylene vinylene. The above polymers can also bemixed together in forming the conductive portion of a yarn.

In one embodiment, a dopant may be added to the conductive polymer inorder to improve conductivity. The dopant, for instance, may comprise ahalide ion, such as a chloride ion, or a bromide ion. Other dopantsinclude perchlorate ions, tetrafluoroborate ions, hexafluoroarsenateions, sulfate ions, nitrate ions, thiocyanate ions, hexafluoride silicicacid ions, trifluoroacetate ions, phosphate ions, phenylphosphate ions,and the like. Particular examples of dopants include hexafluorophosphateions, tosylate ions, ethylbenzene sulfonate ions, alkylbenzene sulfonateions such as dodecylbenzene sulfonate ions, methylsulfonate ions, otheralkyl sulfonate ions, polyacrylic acid ions, polyvinyl sulfonic acidions, polystyrene sulfonate ions,poly(2-acrylamido-2-methylpropanesulfonic acid ions, and the like. Theamount of dopant added to the conductive polymer can vary depending uponthe particular application. For instance, the dopant can be combinedwith the conductive polymer in an amount from about 3% to about 50% byweight, such as from about 10% to about 30% by weight.

In one embodiment, a conductive portion of a multicomponent fiber can beformed by applying a metallic coating to a polymer resin. The polymerresin can comprise any of the conductive polymers described above or cancomprise a non-conductive polymer. In an alternative embodiment, aconductive filler can be loaded into a thermoplastic resin. Thethermoplastic resin can comprise a conductive polymer as described aboveor non-conductive polymer.

Metals well suited for coating a polymer material include gold, silver,chrome, iron, and the like. Conductive particles that may be usedinclude any of the metals described above in addition to aluminum,graphite, other carbon particles, carbon fibers, carbon black, and thelike.

In yet another embodiment, the conductive portion of the multicomponentfiber or filament may comprise a carbon filament.

In one particular embodiment, the electrically conductive compositefiber of the present disclosure includes a conductive polymer layer madeof a thermoplastic polyamide containing from about 13% to about 60% byweight of an electrically conductive particulate matter, such as carbonblack, graphite, boron nitride, or the like. The fiber further includesa non-conductive component made of a thermoplastic polyamide.

In another embodiment, the conductive yarn comprises a thermoplasticpolymer covered with a metal, such as silver or stainless steel. Thethermoplastic polymer may comprise, for instance, a polyamide such asnylon or a polyester.

Multicomponent fibers and yarns made in accordance with the presentdisclosure can include a non-conductive component in addition to aconductive component. The non-conductive component can be made from anysuitable natural or synthetic polymer. For instance, the non-conductiveportion can be made from a polyamide, such as nylon 6 or nylon 66.Alternatively, the non-conductive portion can comprise a polyester, suchas polyethylene terephthalate, polybutylene terephthalate, copolymersthereof, and the like. In yet another embodiment, the non-conductivecomponent may comprise a polyolefin, such as polyethylene orpolypropylene including copolymers thereof. In yet another embodiment,the non-conductive portion may comprise a polyacrylonitrile or apolyvinyl alcohol polymer. The relative amounts of the conductivecomponent in relation to the non-conductive component can vary widelydepending upon various different factors. The amount of the conductivecomponent, for instance, can depend on the conductivity of the materialand the type of materials being used. In general, the conductivecomponent can comprise from about 20% to about 90% of the multicomponentfiber, such as from about 30% to about 70% by weight.

In another embodiment of the present disclosure, the conductive yarn maycomprise a multifilament yarn containing conductive filaments. Forinstance, a multifilament yarn can be formed in which one or moreconductive filaments can be surrounded by non-conductive filaments. Thenon-conductive filaments can be made from any of the non-conductivethermoplastic polymers described above. The conductive filaments, on theother hand, can be made from any of the conductive materials describedabove including conductive polymers, a metallic material, and the like.

In yet another embodiment, a multifilament yarn made from thermoplasticfilaments can be covered with carbon nanotube to render the yarnconductive.

The conductive yarns made in accordance with the present disclosure canbe woven or knitted into any suitable fabric structure capable ofcarrying out the process of the present disclosure. As described above,the fabric structure can be made entirely from conductive yarns.Alternatively, the fabric can be made from a combination of conductiveyarns and non-conductive yarns. For instance, the conductive yarns canbe strategically placed within the fabric in order to form a countlessvariety of different electrical circuits for use in carrying out theprocesses of the present disclosure.

In one embodiment, the fabric structure of the present disclosurecomprises a knitted fabric containing conductive yarns andnon-conductive yarns. In general, any suitable knitting machine may beused in accordance with the present disclosure. For instance, theknitting machine may comprise a weft knitting machine, a warp knittingmachine, or a seamless knitting machine. In one embodiment, forinstance, a Santoni circular knitting machine is used. Knitting machinesfor use in the present disclosure offer various advantages and benefits.For instance, through the use of a knitting machine, a three-dimensionalknitted architecture can be constructed that can advantageously placeconductive yarns in needed locations. In addition, many knittingmachines allow users to select needle-to-needle operationselectronically and can have a variety of different yarn feeders.

In one embodiment, for instance, the fabric is formed or knitted on acircular knitting machine that has a computerized electronic needle andyarn feed selection system. Typically cylindrical blanks are knittedusing both the cylindrical needles and the dial needles. The cylinderneedles knit a first series of courses and the dial needles can knit asecond series of courses.

Alternatively, the knitting machine can include more than two courses.For instance, the knitting machine can include from about two to aboutsixteen courses, such as from about six to about twelve courses.

In one embodiment, a knitting machine can be used with eight feeders. Afabric can be made having a three-dimensional configuration from theknitting machine. For instance, a double-faced fabric can be produced.In this manner, the face of the fabric can include primarily onlynon-conductive yarns, while the back of the fabric can includeconductive yarns. For instance, a plating technique can be used toproduce the fabric. Plating is a knit construction in which two or moreyarns are fed simultaneously. The second yarn is generally of adifferent type than the first yarn. During the knitting process, thesecond yarn is placed under the first yarn so that each yarn can berolled to a specific side of the fabric. In this manner, one yarn canappear primarily on the face of the fabric and the other yarn canprimarily appear on the back of the fabric.

In one embodiment, in addition to a non-conductive yarn and a conductiveyarn, the fabric can include various other yarns. For instance, thefabric can include an elastic yarn that when stretched recovers. Forinstance, the elastic yarn may comprise Spandex.

In one embodiment, for instance, the knitted yarn may be formed fromabout four to about six courses. The first course, for instance, can bemade from a non-conductive yarn, such as polyester, cotton, nylon, anacrylic polymer, or the like. The remaining courses, on the other hand,can comprise a single yarn or a combination of yarns. For instance, oneof the courses can contain a conductive yarn in conjunction with aspandex yarn. A third course, on the other hand, may contain anon-conductive yarn in combination with a spandex yarn. A fourth course,on the other hand, may be made exclusively from the conductive yarn. Alldifferent combinations can be used and all different numbers of coursescan be used to form the fabric. In this manner, a three-dimensionalfabric architecture can be constructed particularly well suited forconstructing electric circuits within the fabric and for the fabric tocarry out the commands that are user inputted. During knitting, floatloops can be used in order to obtain the desired construction.

In implementations wherein the interactive device 102 and/or theinteractive device 104 are smart garments constructed in a suitablemanner as described above, the smart garments can be configured toperform suitable functionality in accordance with example aspects of thepresent disclosure. For instance, the smart garment can be configured todetect input gestures performed by a user with respect to the smartgarment. For instance, the user may perform a suitable touch gesture,hand gesture, etc. on a surface of the smart garment. The electricallyconductive fibers of the smart garment can facilitate a detection of theinput gesture by the input gesture detector associated with theinteractive device. In this manner, the detection sensor(s) 114 can beelectrically coupled to one or more of the electrically conductivefibers of the smart garment to form one or more electrical circuitsconfigured to detect the input gesture as performed with respect to thesmart garment.

Similarly, the one or haptic feedback devices 116 can further beimplemented within the smart garment, and can be configured to providesuitable emotive contextual signals to the user in accordance withexample aspects of the present disclosure. In some implementations, thehaptic feedback device(s) implemented within the smart garment caninclude one or more actuators, engines, motors, etc. configured toprovide the emotive contextual signals. In such implementations, thehaptic feedback device(s) 116 can be electrically coupled to one or moreelectrically conductive fibers of the smart garment. In someimplementations, the haptic feedback device(s) 116 can be one or moreyarns of the smart garment. Such yarns of the smart garment can beconfigured to provide emotive contextual signals in accordance withexample aspects of the present disclosure. For instance, the yarns canbe configured to apply heat to the user through one or more electricalcircuits formed by the yarns. As another example, the yarns can beconfigured to actuate to change the form of the smart garment. Forinstance, the yarns can be configured to actuate to tighten or loosenthe smart garment around a wearer of the smart garment to provide asuitable mediated interaction.

Further still, the smart garment can be configured to monitor one ormore biometric characteristics of the user, for instance, using the oneor more biometric monitors 118 implemented within or with respect to thesmart garment. In this manner, such biometric monitors 118 can beelectrically coupled to one or more electrically conducting yarns of thesmart garment to form one or more suitable circuits for monitoringsuitable biometric characteristics of a wearer of the smart garment.

It will be appreciated that various suitable smart garments can be usedin accordance with example aspects of the present disclosure. Such smartgarments can be associated with one or more computing devices, sensors,feedback devices, etc. used to carry out example aspects of the presentdisclosure. In this manner, the smart garments constructed according toexample aspects of the present disclosure, in association with asuitable computing device (e.g. having a suitable processor(s), memorydevice(s), etc. can be configured to be worn by a user, and to implementfunctionality of the present disclosure.

FIG. 2 depicts an example configuration of a system 200 for providingemotive contextual signals. The system 200 includes a first interactivedevice 202 and a second interactive device 204. In some implementations,the first interactive device 202 and the second interactive device 204can respectively correspond to the first interactive device 102 and thesecond interactive device 104 depicted in FIG. 1. The first interactivedevice 202 can be communicatively coupled to a first user device 206,and the second interactive device 204 can be communicatively coupled toa second user device 208. For instance, the first interactive device 202can be coupled to the first user device 206 via a network such as aBluetooth network, Wi-Fi Direct network or other suitable network.Similarly, the second interactive device 204 can be communicativelycoupled to a second user device 208 via a network such as a Bluetoothnetwork, Wi-Fi Direct network or other suitable network.

Communication between the first interactive device 202 and the secondinteractive device 204 can be facilitated via the first user device 206and the second user device 208. For instance, the first user device 206and the second user device 208 can relay data communicated between thefirst interactive device 202 and the second interactive device 204. Thefirst user device 206 and the second user device 208 can communicate viaa network 210 (e.g. the Internet). In this manner the first interactivedevice 202 can provide data to the first user device 206. The first userdevice 206 can provide the data to the second user device 208 via thenetwork 210. The second user device 208 can provide the data to thesecond interactive device 204.

In some implementations, the first user device 206 and/or the seconduser device 208 can communicate with a remote computing device 212, forinstance, via the network 210. The remote computing device 212 can be aserver, such as a web server. One or more example aspects of the presentdisclosure can be performed by the remote computing device 212. Forinstance, the signal determiner 108 and/or the signal determiner 112 canbe implemented in the remote computing device 212. In this manner, dataindicative of an input gesture performed by a user can be provided tothe remote computing device 212 (e.g. from the first interactive device202 or the second interactive device 204), and the signal determiner(s),as implemented in the remote computing device 212 can determine one ormore emotive contextual signals to be provided to the first interactivedevice 202 and/or the second interactive device 204 in accordance withexample aspects of the present disclosure.

In some implementations, the first user device 206 and the second userdevice 208 can facilitate a registration or pairing between the firstinteractive device 202 and the second interactive device 204. Forinstance, a first user associated with the first interactive device 202can interact with the first user device 206 to establish communicationsbetween the first user device 206 and the first interactive device 202,as well as to establish communications between the first interactivedevice 202 and the second interactive device 204. Similarly, a seconduser associated with the second interactive device 204 can interact withthe second user device 208 to establish communications between thesecond user device 208 and the second interactive device 204, as well asto establish communications between the second interactive device 204and the first interactive device 202. In this manner the first user canestablish a mediated social interaction with the second user, or viceversa.

It will be appreciated that the systems 100 and 200 depicted in FIGS. 1and 2 respectively are depicted for illustrative purposes. Further, itwill be appreciated that any suitable system configuration can be usedto implement the example aspects of the present disclosure. Forinstance, the first interactive device 202 may communicate directly withthe second interactive device 204. As another example, one or moreexample aspects of the present disclosure can be performed by the firstuser device 206 and/or the second user device 206. In someimplementations, mediated social interactions can be established betweenmore than two interactive devices. For instance, one or more additionalinteractive devices associated with one or more additional users can beincluded in the system. The one or more additional interactive devicescan be configured to communicate with the first interactive device 202and/or the second interactive device 204 via the network 210 and/or oneor more additional user devices respectively associated with the one ormore additional interactive devices. In this manner, mediated socialinteractions can be established between any suitable number of users.

FIG. 3 depicts a flow diagram of an example method (300) of providingemotive contextual signals. The Method (300) can be implemented by oneor more computing devices, such as one or more of the computing devicesdepicted in FIG. 5. In particular implementations, the method (300) canbe implemented by the input gesture detector 106 and the signaldeterminer 108 depicted in FIG. 1. In addition, FIG. 3 depicts stepsperformed in a particular order for purposes of illustration anddiscussion. Those of ordinary skill in the art, using the disclosuresprovided herein, will understand that the steps of any of the methodsdiscussed herein can be adapted, rearranged, expanded, omitted, ormodified in various ways without deviating from the scope of the presentdisclosure.

At (302), the method (300) can include receiving a user input from afirst user. The user input can be an input gesture indicative of arequest to facilitate a provision of emotive contextual signals to asecond user. For instance, the input gesture can be any suitable inputgesture, such as a hand gesture, a touch gesture, a motion gesture, anapplication of pressure, an input using one or more suitable inputdevices (e.g. keyboard, mouse, trackpad, etc.), or other suitable inputgesture. The input gesture can be performed with respect to a firstinteractive device associated with the first user. The first interactivedevice can be any suitable computing device capable of implementingexample aspects of the present disclosure. In this manner, the firstinteractive device can be any suitable computing device configured toprovide emotive contextual signals to a user in accordance with exampleaspects of the present disclosure. For instance the first interactivedevice can be a general purpose computer, special purpose computer,laptop, desktop, mobile device, navigation system, smartphone, tablet,wearable computing device (e.g. smart garment, fitness band, smartwatch, etc.), a display with one or more processors, or other suitablecomputing device

At (304), the method (300) can include determining a mediated socialinteraction based at least in part on the user input. The mediatedsocial interaction can be determined based at least in part on the userinput. For instance, the mediated social interaction can be mapped tothe input gesture as part of a gesture mapping scheme that corresponds aplurality of suitable input gestures to a plurality of mediated socialinteractions and/or emotive contextual signals. For instance, thegesture mapping scheme can be specified within a lookup table or othersuitable data structure. In this manner, determining the mediated socialinteraction can include accessing the gesture mapping scheme.

The mediated social interaction can be any suitable mediated socialinteraction, such as a mediated physical interaction. The mediatedsocial interaction can be associated with an evocation of an emotionalor biometric response within a user. For instance, the mediated socialinteraction can be associated with an evocation of a feeling of warmth,a calming or soothing feeling, a feeling of connectedness, a feeling ofintimacy, or other suitable emotion. In some implementations, themediated social interaction can be associated with a simulation of aparticular action or behavior. The mediated social interaction can beassociated with a particular form of touch or contact. For instance, themediated social interaction can be associated with a simulation ofholding hands, hugging, breathing, or other suitable behavior or action.

At (306), the method (300) can include determining one or more emotivecontextual signals based at least in part on the mediated socialinteraction. For instance, the emotive contextual signals can bedetermined such that an application of the emotive contextual signalswill bring about the desired mediated social interaction. For instance,the emotive contextual signals can attempt to simulate a particularbehavior or action associated with the mediated social interaction. Theemotive contextual signals can further attempt to stimulate an emotionalor biometric response associated with the mediated social interaction.

The emotive contextual signals can be haptic feedback signals. Forinstance, such haptic feedback signals can include vibration, pressure,temperature (e.g. heat or warmth), electrical currents, forces, stress,strain, impacts, and/or other suitable forms of haptic feedback to beapplied to the second user. It will be appreciated that the emotivecontextual signals can be any other suitable forms of physicalstimulation. In this manner, the emotive contextual signals can includeany suitable combination of haptic feedback signals or other physicalstimulations to achieve the desired mediated social interaction. As willbe described in more detail below with regard to FIG. 4, in someimplementations, the emotive contextual signals can be determined basedat least in part on one or more biometric signals (e.g. heart rate, skinconductance, body temperature, etc.) associated with the second user. Inthis manner, the emotive contextual signals can be personalized for theuser to establish the mediated social interaction based at least in parton the user's biometric characteristics.

In implementations wherein the interactive device is a smart garmentaccording to example aspects of the present disclosure, the emotivecontextual signals can include one or more signals provided by the smartgarment. For instance, such signals can be provided by one or moreactuators, motors, vibration engines, etc. electrically coupled to oneor more conductive yarns of the smart garment. In some implementations,one or more yarns of the smart garment can be configured to provideemotive contextual signals. For instance, such one or more yarns can beconfigured to implement a circuit to provide heat to a wearer of thesmart garment. As another example, such yarns can be implemented withina circuit to cause the yarns to actuate or compress, such that a fit ofthe smart garment with respect to the user can be adjusted (e.g.tightened or loosened).

In some implementations, one or more emotive contextual signals canfurther be determined for the first user. For instance, in instanceswherein the mediated social interaction includes two-way contact, suchas holding hands or hugging, the emotive contextual signals associatedwith such two-way contact can be determined for each user. In thismanner, the emotive contextual signals can be applied to each user, suchthat each user experiences the mediated social interaction. In suchimplementations, the emotive contextual signals determined for the firstuser can be determined based at least in part on one or more biometricsignals associated with the first user.

At (308), the method (300) can include providing the one or more emotivecontextual signals to the second user. For instance, the one or moreemotive contextual signals can be provided to the second user using oneor more haptic feedback devices associated with an interactive device.Such haptic feedback devices can include one or more actuators, motors,vibration engines, electrically conductive yarns associated with a smartgarment etc. The emotive contextual signals can be applied to the seconduser while the second user is making physical contact with theinteractive device associated with the second user. In this manner, theemotive contextual signals can be applied to the skin of the seconduser.

FIG. 4 depicts a flow diagram of an example method (400) of determiningemotive contextual signals according to example embodiments of thepresent disclosure. The Method (400) can be implemented by one or morecomputing devices, such as one or more of the computing devices depictedin FIG. 5. In particular implementations, the method (400) can beimplemented by the input gesture detector 106 and the signal determiner108 depicted in FIG. 1. In addition, FIG. 4 depicts steps performed in aparticular order for purposes of illustration and discussion.

At (402), the method (400) can include monitoring one or more biometriccharacteristics associated with a user. The user can be a user to whichemotive contextual signals are to be applied. For instance, the user canbe the second user described with regard to FIG. 3. The one or morebiometric characteristics can be associated with biometric signals ofthe user, such as heart rate, body temperature, skin conductance, orother suitable biometric signal. The biometric characteristics can bemonitored by an interactive device associated with the user. Forinstance, the interactive device can monitor the biometriccharacteristics using one or more biometric monitors while the user ismaking contact with the interactive device.

At (404), the method (400) can include determining one or more firstemotive contextual signals based at least in part on the one or morebiometric characteristics. For instance, the emotive contextual signalscan include one or more haptic feedback signals or other physicalstimulations designed to implement a mediated social interaction betweenthe user and one or more additional users. For instance, particularbiometric characteristics respond differently to different emotivecontextual signals. In this manner, the emotive contextual signalsdetermined to establish a particular mediated social interaction canvary based on the biometric characteristics of the user to whom theemotive contextual signals are to be applied.

In some implementations, the mediated social interaction can be designedto evoke a particular biometric response from the user or to bring thebiometric characteristics of the user to a particular state or provide atarget response. In this manner, the monitored biometric characteristicscan be used to determine the emotive contextual signals that can be usedto achieve such goals.

At (406), the method (400) can include providing the one or more firstemotive contextual signals to the user. For instance, the first emotivesignals can be provided to the user via one or more haptic feedbackdevices associated with the interactive device.

At (408), the method (400) can include identifying a biometric responseof the second user that occurs in response to the provision of the oneor more first emotive contextual signals to the user. For instance, thebiometric characteristics of the user can change in response toreceiving the emotive contextual signals. In this manner, identifyingthe biometric response can include comparing the biometriccharacteristics of the user at a first point in time prior to theprovision of the emotive contextual signals to the biometriccharacteristics of the user at a second point in time subsequent to theprovision of the emotive contextual signals. The biometric response cancorrespond to the change in the biometric characteristics of the user atthe second time relative to the first time.

At (410), the method (400) can include determining one or more secondemotive contextual signals to be provided to the user based at least inpart on the biometric response. The second emotive contextual signalscan include one or more different haptic feedback signals or one or moredifferent haptic feedback signal combinations relative to the firstemotive contextual signals. For instance, the emotive contextual signalscan evoke an unintended biometric and/or emotional response in the user.In such instances, the emotive contextual signals can be adjusted tocorrect such unintended response(s). In this manner, the emotivecontextual signals can be adjusted to more accurately facilitate theintended effects of the intended mediated social interaction.

In some implementations, the biometric response of the user can be usedto “learn” personalized emotive contextual signals that are bettertailored for the user. For instance, the biometric responses of the usercan be analyzed with respect to a plurality of emotive contextualsignals provided to the user over time to learn how the user responds tothe emotive contextual signals. Such learning techniques can be used topredict a user response to future provisions of emotive contextualsignals. In this manner, various emotive contextual signals or emotivecontextual signal combinations can be mapped to various mediated socialinteractions based on the tracked user responses to such emotivecontextual signals. In some implementations, such learning and/ormapping techniques can be implemented using machine learning techniques.For instance, a suitable machine learning model (e.g. neural network orother suitable model) can be trained based on the user's biometricresponses, and can be used to determine emotive contextual signals to beprovided to the user for various mediated social interactions.

At (412), the method (400) can include providing the one or more secondemotive contextual signals to the user. For instance, the emotivecontextual signals can be provided to the user via the one or morehaptic feedback devices associated with the interactive device of theuser.

FIG. 5 depicts an example computing system 500 that can be used toimplement the methods and systems according to example aspects of thepresent disclosure. The system 500 can be implemented using aclient-server architecture that includes an interactive device 510 thatcommunicates with one or more remote devices 530 over a network 540. Thesystem 500 can be implemented using other suitable architectures.

The system 500 includes an interactive device 510, The interactivedevice 510 can be, or can be associated with, any suitable computingdevice, such as a general purpose computer, special purpose computer,laptop, desktop, mobile device, navigation system, smartphone, tablet,wearable computing device, a display with one or more processors, orother suitable computing device. In some implementations, theinteractive device 510 can be a smart garment in accordance with exampleaspects of the present disclosure. The interactive device 510 can haveone or more processors 512 and one or more memory devices 514. Theinteractive device 510 can also include a network interface. The networkinterface can be used to communicate with one or more user devices 550over a network, such as a direct network (e.g. Bluetooth network, Wi-Fidirect network, etc.). In some implementations, the network interfacecan be used to communicate with one or more remote devices 530 over thenetwork 540. The network interface can include any suitable componentsfor interfacing with one more networks, including for example,transmitters, receivers, ports, controllers, antennas, or other suitablecomponents.

The one or more processors 512 can include any suitable processingdevice, such as a microprocessor, microcontroller, integrated circuit,logic device, graphics processing units (GPUs) dedicated to efficientlyrendering images or performing other specialized calculations, and/orother suitable processing device. The one or more memory devices 514 caninclude one or more computer-readable media, including, but not limitedto, non-transitory computer-readable media, RAM, ROM, hard drives, flashdrives, or other memory devices. The one or more memory devices 514 canstore information accessible by the one or more processors 512,including computer-readable instructions 516 that can be executed by theone or more processors 512. The instructions 516 can be any set ofinstructions that when executed by the one or more processors 512, causethe one or more processors 512 to perform operations. For instance, theinstructions 516 can be executed by the one or more processors 512 toimplement the input gesture detector 106 and the signal determiner 108described with reference to FIG. 1.

As shown in FIG. 5, the one or more memory devices 514 can also storedata 518 that can be retrieved, manipulated, created, or stored by theone or more processors 512. The data 518 can include, for instance,gesture mapping data, emotive contextual signals data generatedaccording to example aspects of the present disclosure, and other data.The data 518 can be stored locally at the interactive device 510 and/orremote from the interactive device 510, such as in one or moredatabases. The one or more databases can be implemented within theserver 530, or can be connected to the interactive device 510 by a highbandwidth LAN or WAN, or can also be connected to interactive device 510through network 540. The one or more databases can be split up so thatthey are located in multiple locales.

The interactive device 510 can include various input/output devices forproviding and receiving information from a user, such as a touch screen,touch pad, data entry keys, speakers, and/or a microphone suitable forvoice recognition. For instance, the interactive device 510 can have adisplay device for presenting a user interface. The interactive devicecan further include one or more detection sensors 114 configured todetect an input gesture performed by a user in accordance with exampleaspects of the present disclosure, haptic feedback devices 116configured to provide emotive contextual signals in accordance withexample embodiments of the present disclosure, and one or more biometricmonitors 118 configured to monitor one or more biometric characteristicsof the user in accordance with example aspects of the presentdisclosure.

The interactive device can further include a prediction model 552. Theprediction model 552 can be a suitable machine learning model configuredto receive a mediated social interaction and/or one or more biometriccharacteristics of a user as input and to provide one or more emotivecontextual signals corresponding to the mediated social interaction asoutput. In this manner, the prediction model 552 can predict one or moreemotive contextual signals that will effectuate the selected mediatedsocial interaction for the user. The prediction model 552 can be trainedusing suitable training data, and can be adjusted based at least in parton biometric responses of the user to various provisions of variousemotive contextual signals over one or more periods of time. Theprediction model can be trained by a training system configured toimplement one or more suitable training techniques, such as, forexample, backwards propagation of errors. The training system can beimplemented, for instance, by the remote device 530, the user device550, the interactive device 510, or in other suitable location. Theprediction model can be used by the signal determiner 108 to determinesuitable emotive contextual signals to be provided to a user. In someimplementations, the prediction model 552 can be implemented at theremote computing device 530, the user device 550, or at other suitablelocations.

The interactive device 510 can exchange data with one or more userdevices 550 (e.g. over a direct network) and/or with one or more remotedevices 530 over the network 540. For instance, a remote device can be aserver, such as a web server. A user device can be any suitable userdevice, such as a smartphone, tablet, laptop, desktop, wearablecomputing device, etc. The system 500 can include any suitable number ofinteractive devices 510, user devices 550 and/or remote devices 530. Theremote devices 530 can be connected to the interactive device 510 overthe network 540.

Similar to the interactive device 510, a remote device 530 and/or a userdevice 550 can include one or more processor(s) 532 and a memory 534.The one or more processor(s) 532 can include one or more centralprocessing units (CPUs), and/or other processing devices. The memory 534can include one or more computer-readable media and can storeinformation accessible by the one or more processors 532, includinginstructions 536 that can be executed by the one or more processors 532and data 538.

In some implementations, one or more of the input gesture detector 106or the signal determiner 108 can be implemented by a remote device 530and/or a user device 550. In this manner, the functionality associatedwith the one or more of the input gesture detector 106 or the signaldeterminer 108 can be performed by a remote device 530 and/or a userdevice 550. For instance, the interactive device 510 can communicatewith a remote device 530 and/or a user device 550 to implement exampleaspects of the present disclosure.

The remote device(s) 530 can also include a network interface used tocommunicate with one or more remote computing devices (e.g. interactivedevice 510) over the network 540. The network interface can include anysuitable components for interfacing with one more networks, includingfor example, transmitters, receivers, ports, controllers, antennas, orother suitable components.

The network 540 can be any type of communications network, such as alocal area network (e.g. intranet), wide area network (e.g. Internet),cellular network, or some combination thereof. The network 540 can alsoinclude a direct connection between a remote device 530 and theinteractive device 510. In general, communication between theinteractive device 510 and a remote device 530 can be carried vianetwork interface using any type of wired and/or wireless connection,using a variety of communication protocols (e.g. TCP/IP, HTTP, SMTP,FTP), encodings or formats (e.g. HTML, XML), and/or protection schemes(e.g. VPN, secure HTTP, SSL).

The technology discussed herein makes reference to servers, databases,software applications, and other computer-based systems, as well asactions taken and information sent to and from such systems. One ofordinary skill in the art will recognize that the inherent flexibilityof computer-based systems allows for a great variety of possibleconfigurations, combinations, and divisions of tasks and functionalitybetween and among components. For instance, server processes discussedherein may be implemented using a single server or multiple serversworking in combination. Databases and applications may be implemented ona single system or distributed across multiple systems. Distributedcomponents may operate sequentially or in parallel.

While the present subject matter has been described in detail withrespect to specific example embodiments thereof, it will be appreciatedthat those skilled in the art, upon attaining an understanding of theforegoing may readily produce alterations to, variations of, andequivalents to such embodiments. Accordingly, the scope of the presentdisclosure is by way of example rather than by way of limitation, andthe subject disclosure does not preclude inclusion of suchmodifications, variations and/or additions to the present subject matteras would be readily apparent to one of ordinary skill in the art.

What is claimed is:
 1. A computer-implemented method of providingemotive contextual signals to a user, the method comprising: receiving,by a first computing device, a user input from a first user indicativeof a request to facilitate a provision of emotive contextual signals toa second user; determining, by a second computing device, one or morefirst emotive contextual signals to be provided to the second user basedat least in part on the user input, the one or more first emotivecontextual signals comprising one or more first haptic signals intendedto facilitate a mediated social interaction associated with the seconddetermining, by the second computing device, an emotional response ofthe second user to the one or more first emotive contextual signals; andcomparing, by the second computing device, the determined emotionalresponse of the second user to a target emotional response.
 2. Thecomputer-implemented method of claim 1, further comprising providing; bythe second computing device, the one or more first emotive contextualsignals to the second user.
 3. The computer-implemented method of claim1, wherein the user input comprises an input gesture performed by thefirst user with respect to the first computing device, the input gesturebeing associated with the mediated social interaction.
 4. Thecomputer-implemented method of claim 3, wherein the input gesturecomprises a physical interaction by the first user with the firstcomputing device.
 5. The computer-implemented method of claim 3, whereinthe first computing device comprises one or more gesture detectionsensors, and wherein receiving the user input comprises detecting theinput gesture via the one or more gesture detection sensors.
 6. Thecomputer-implemented method of claim 1, wherein the second computingdevice comprises one or more haptic devices and wherein determining oneor more first emotive contextual signals comprises determining the oneor more first haptic signals to be provided to the second user by theone or more haptic devices.
 7. The computer-implemented method of claim1, further comprising determining, by the second computing device, oneor more second emotive contextual signals based at least in part on thecomparison of the determined emotional response to the target emotionalresponse.
 8. The computer-implemented method of claim 1, whereindetermining, by the second computing device, an emotional response ofthe second user to the one or more first emotive contextual signalscomprises measuring, by the second computing device, one or morebiometric signals associated with the second user.
 9. Thecomputer-implemented method of claim 8, wherein the one or morebiometric signals comprise one or more of a heart rate associated withthe second user, a temperature associated with the second user, or askin conductance associated with the second user.
 10. Thecomputer-implemented method of claim 1, wherein the first and secondcomputing devices are associated with smart garments having a pluralityof electrically conductive yarns configured to implement one or morecircuits.
 11. The computer-implemented method of claim 1, whereindetermining, by a second computing device, one or more first emotivecontextual signals comprises determining the one or more first emotivecontextual signals using one or more machine learning techniques. 12.The computer-implemented method of claim 1, wherein determining, by thesecond computing device, one or more first emotive contextual signals tobe provided to the second user comprises determining the one or morefirst emotive contextual signals based at least in part on one or morecharacteristics of the second user.
 13. A computing system, comprising:one or more processors; and one or more memory devices, the one or morememory devices storing compute readable instructions that when executedby the one or more processors cause the one or more processors toperform operations, the operations comprising: receiving a user inputfrom a first user indicative of a request to facilitate a provision ofemotive contextual signals to a second user; determining one or morefirst emotive contextual signals to be provided to the second user basedat least in part on the user input, the one or more first emotivecontextual signals comprising one or more first haptic signals intendedto facilitate a mediated social interaction associated with the seconduser; determining an emotional response of the second user to the one ormore first emotive contextual signals; and comparing the determinedemotional response of the second user to a target emotional response.14. The computing system of claim 13, further comprising one or morehaptic devices, and wherein the operations further comprise providingthe one or more first emotive contextual signals to the second user viathe one or more haptic devices.
 15. The computing system of claim 13,the operations further comprising determining one or more second emotivecontextual signals based at least in part on the comparison of thedetermined emotional response to the target emotional response.
 16. Oneor more tangible, non-transitory computer-readable media storingcomputer-readable instructions that when executed by one or moreprocessors cause the one or more processors to perform operations, theoperations comprising: receiving a user input from a first userindicative of a request to facilitate a provision of emotive contextualsignals to a second user; and determining one or more first emotivecontextual signals to be provided to the second user based at least inpart on the user input and one or more characteristics of the seconduser, the one or more first emotive contextual signals comprising one ormore first haptic signals intended to facilitate a mediated socialinteraction associated with the second user.
 17. The one or moretangible, non-transitory computer-readable media of claim 16, whereinthe user input comprises an input gesture performed by the first userwith respect to the first computing device, the input gesture beingassociated with the first emotional response.
 18. The one or moretangible, non-transitory computer-readable media of claim 16, whereindetermining one or more first emotive contextual signals comprisesdetermining the one or more first emotive contextual signals based atleast in part on one or more biometric characteristics of the seconduser.